Recent modeling advances successfully derived time varying estimates of nonlinear heartbeat dynamics, whose quantifiers mainly rely on first-order moments (i.e., average over time). Nevertheless, while these metrics account for the information carried by the tonic (slow trend) nonlinear dynamics, they fail to quantify potentially meaningful information nested in the superimposed phasic (high frequency) activity of the physiological series. In this study, we investigate new metrics from phasic activity of time-varying bispectra, which are derived from nonlinear point-process modeling of heartbeat dynamics. Instantaneous phasic activity is derived using wavelet decomposition of time-varying bispectra, and quantified using the area under the c...